Nature CommunicationsBioinformaticsPeer-reviewed journal article
Spatially Interacting Phosphorylation Sites and Mutations in Cancer
Kuan‐lin HuangiD, Adam David ScottiD, Daniel Cui ZhouiD, Liang-Bo WangiD, Amila WeerasingheiD, Abdülkadir ElmasiD, Ruiyang LiuiD, Yige WuiD, Michael C. WendliD, Matthew A. WyczalkowskiiD, Jessika Baral, Sohini SenguptaiD, Chin‐Wen LaiiD, Kelly V. RugglesiD, Samuel H. PayneiD, Benjamin J. RaphaeliD, David FenyöiD, Ken CheniD, Gordon Brent MillsiD, Li DingiD
Abstract
Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1,255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1,000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance.
- assay: proteomics
- research focus: gene regulatory network inference
- research focus: variant effect prediction
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- Citations
- 24
- FWCI
- 1.69
- Field percentile
- top 17%
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